library(openxlsx)
# allC = merge(p1C,p2C,by.x="Sample",by.y="Sample")
popsOfInterestFile="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/finalCounts/popsOfInterest.txt"
popsOfInterest=read.delim(popsOfInterestFile, stringsAsFactors = FALSE, sep = "\t")
popsOfInterest$POPCOMP=gsub(" ",".",popsOfInterest$POPCOMP)
popsOfInterest$POPF=gsub(" ",".",popsOfInterest$POPF)
popsOfInterest$POPHRS1000=gsub(" ",".",popsOfInterest$POPHRS1000)
popsOfInterest$POPM=gsub(" ",".",popsOfInterest$POPM)
# popsOfInterest$POPM=gsub(")",".",popsOfInterest$POPM,fixed = TRUE)
# popsOfInterest$POPM=gsub("(",".",popsOfInterest$POPM,fixed = TRUE)
popsOfInterest$POPJ=gsub(" ",".",popsOfInterest$POPJ)
popsOfInterest$POPJ=gsub(")",".",popsOfInterest$POPJ,fixed = TRUE)
popsOfInterest$POPJ=gsub("(",".",popsOfInterest$POPJ,fixed = TRUE)
releasedFile="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/FULL/releasedSamples.txt"
released = read.delim(releasedFile,
header = TRUE,
stringsAsFactors = FALSE)
noBadsFile="/Users/Kitty/git/auto-fcs/explore/openCyto/extractManualComp/manualUse.txt"
noBads = read.delim(noBadsFile,
header = TRUE,
stringsAsFactors = FALSE)
dir="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/finalCountsFreqCBC/"
p1="p1.cnts.frqs.cbcs.xlsx"
p2="p2.cnts.frqs.cbcs_update.xlsx"
addCols=c("Sample", "Manual", "MACHINE", "F_ID", "DATE", "EXPERIMENTER")
sheets = list(c("COUNTS",1),c("FREQ",2),c("CBCS",3))
parse <- function(dir,p,sheet,extractPop,addCols,manualRms) {
pd= read.xlsx(paste0(dir,p), sheet=as.numeric(sheet[2]))
extract = c(addCols,extractPop[!is.na(extractPop)])
have=( extract %in% colnames(pd))
print(table(have))
print(extract[have])
pE = pd[,extract[have]]
pE$METRIC=sheet[1]
#
use = (pE$F_ID %in% manualRms$Study.ID)
pE = pE[use,]
return(pE)
}
p1All=data.frame()
p2All=data.frame()
p1Filt = read.xlsx(paste0(dir,p1), sheet=1)
namesP1=p1Filt[which(p1Filt$`Live.cells.(PE-)`>20000),]$Sample
p2Filt = read.xlsx(paste0(dir,p2), sheet=1)
namesP2=p2Filt[which(p2Filt$`Live.Single.PBMCs`>20000),]$Sample
for(sheet in sheets){
p1d=parse(dir=dir,p=p1,sheet=sheet,extractPop =popsOfInterest$POPM,addCols = addCols,manualRms=released )
usep1=p1d$Sample %in% namesP1
# p1d=p1d[usep1,]
p1All=rbind(p1All,p1d)
p2d=parse(dir=dir,p=p2,sheet=sheet,extractPop =popsOfInterest$POPCOMP,addCols = addCols,manualRms=released )
usep2=p2d$Sample %in% namesP2
# p2d=p2d[usep2,]
#
# usep2=p2d$Sample %in% noBads$x
# p2d=p2d[usep2,]
print(colnames(p2d))
print(colnames(p2All))
p2All=rbind(p2All,p2d)
}
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## character(0)
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
# p2All[which(p2All$DC>60000&p2All$METRIC=="COUNTS"),]$F_ID
popsOfInterest$PANEL1= popsOfInterest$POPM %in% colnames(p1All)
popsOfInterest$PANEL2= popsOfInterest$POPCOMP %in% colnames(p2All)
p1JflowCounts= read.delim("/Volumes/Beta/data/flow/compManual/p1.cnts.xln", stringsAsFactors = FALSE)
p1JflowCounts$Sample=p1JflowCounts$FILE
p2JflowCounts= read.delim("/Volumes/Beta/data/flow/compManual/p2.cnts.xln", stringsAsFactors = FALSE)
p2JflowCounts$Sample=p2JflowCounts$FILE
origPercents =read.xlsx("/Volumes/Beta/data/flow/HRS1000 REPORT.xlsx", sheet=1)
origCBCs =read.xlsx("/Volumes/Beta/data/flow/HRS1000 REPORT.xlsx", sheet=3)
origPercentP2 =read.xlsx("/Volumes/Beta/data/flow/p2.newGateTree.xlsx", sheet=2)
origPercentP2$Sample=gsub(".*/","",origPercentP2$X1)
library(ggplot2)
t2 <- theme(
axis.line = element_line(colour = "black"),
axis.text = element_text(colour = "black"),
axis.ticks = element_line(colour = "black"),
# panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
# panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
# legend.position="none",
axis.text.x=element_text(angle=90,hjust=1)
)
theme_set(theme_grey(base_size = 18))
summarize <- function(oc,manual,mergeOCCol,mergeManCol,ocCol,manualCol) {
merge=merge(oc,manual,by.x=mergeOCCol,by.y=mergeManCol)
print(table(merge$Manual))
numManuals=length(merge[which(merge$Manual=="1"),][,ocCol])
merge=merge[which(merge$Manual=="0"),]
t1 =cor.test(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)]),method = "pearson",na.action="na.omit")
t2=cor.test(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)]),method = "spearman",na.action="na.omit")
medianOCFreq=median(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
meanOCFreq=mean(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
sdOCFreq=sd(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
# print(plot(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)])))
medianManualFreq=median(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
meanManualFreq=mean(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
sdManualFreq=sd(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
g= ggplot(merge,aes(x=as.numeric(merge[,c(ocCol)]),y=as.numeric(merge[,c(manualCol)]))) +
geom_point() +
xlab(paste0("OC ",ocCol)) +
ylab(paste0("Manual ",ocCol))+ggtitle(paste0("pearson = ",t1$estimate, "\n spearman = ", t2$estimate, "\nn=", length(merge[,c(ocCol)]) ))
print(g)
tmp = data.frame(
OC_POP = ocCol,
ManualPop = manualCol,
N = length(merge[,c(ocCol)]),
PEARSON = t1$estimate,
SPEARMAN = t2$estimate,
MEDIAN_OC = medianOCFreq,
MEDIAN_MANUAL = medianManualFreq,
ABS_DIFF_MEDIAN = abs(medianOCFreq-medianManualFreq),
MEAN_OC = meanOCFreq,
MEAN_MANUAL = meanManualFreq,
ABS_DIFF_MEAN = abs(meanOCFreq-meanManualFreq),
SD_OC = sdOCFreq,
SD_MANUAL = sdManualFreq,
ABS_DIFF_SD = abs(sdOCFreq-sdManualFreq),
NUM_MANUALS_REMOVED=numManuals
)
return(tmp)
}
results=data.frame()
for(pop in popsOfInterest$POPM){
if(!is.na(pop)){
for(metric in sheets){
jflow=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPJ
origColumn=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPHRS1000
compLook=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPM
if(popsOfInterest[which(popsOfInterest$POPM==pop),]$PANEL1){
print(paste0(pop," panel1 ",metric[1]))
if(metric[1]=="COUNTS"){
tmp =summarize(p1All[which(p1All$METRIC==metric[1]),],p1JflowCounts,"Sample","Sample",pop,jflow)
tmp$METRIC=metric[1]
tmp$PANEL="panel1"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=NA
tmp$COMP_LOOK=compLook
results=rbind(results,tmp)
} else if(metric[1]=="FREQ"){
useOrigPercents =origPercents[which(origPercents[,c(origColumn)]<1000),]
tmp =summarize(p1All[which(p1All$METRIC==metric[1]),],useOrigPercents,"F_ID","Study.ID",pop,origColumn)
tmp$METRIC=metric[1]
tmp$PANEL="panel1"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=length(origPercents[,c(origColumn)])-length(useOrigPercents[,c(origColumn)])
tmp$COMP_LOOK=compLook
results=rbind(results,tmp)
}
}else if(popsOfInterest[which(popsOfInterest$POPM==pop),]$PANEL2){
print(paste0(pop," panel2 ",metric[1]))
if(metric[1]=="COUNTS"){
tmp =summarize(p2All[which(p2All$METRIC==metric[1]),],p2JflowCounts,"Sample","Sample",popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP,jflow)
tmp$METRIC=metric[1]
tmp$PANEL="panel2"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=NA
tmp$COMP_LOOK=compLook
results=rbind(results,tmp)
} else if(metric[1]=="FREQ"){
ocColumnTmp=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP
useOrigPercents =origPercentP2[which(origPercentP2[,c(ocColumnTmp)]<1000),]
origTmp=ocColumnTmp
if(ocColumnTmp==origTmp){
ocColumnTmp=paste0(ocColumnTmp,".x")
origTmp=paste0(origTmp,".y")
}
tmp =summarize(p2All[which(p2All$METRIC==metric[1]),],origPercentP2,"Sample","Sample",ocColumnTmp,origTmp)
tmp$METRIC=metric[1]
tmp$PANEL="panel2"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=length(origPercentP2[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])-length(useOrigPercents[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])
tmp$COMP_LOOK=compLook
results=rbind(results,tmp)
}
}
}
}
}
## [1] "naive.Bcells.(CD27-.IgD+) panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "naive.Bcells.(CD27-.IgD+) panel1 FREQ"
##
## 0 1
## 927 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "naive.Bcells.(CD27-.IgD+) panel1 CBCS"
## [1] "cytotoxic.Tcells-CD8+ panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "cytotoxic.Tcells-CD8+ panel1 FREQ"
##
## 0 1
## 927 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "cytotoxic.Tcells-CD8+ panel1 CBCS"
## [1] "Tcells.(CD3+.CD19-) panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Tcells.(CD3+.CD19-) panel1 FREQ"
##
## 0 1
## 927 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Tcells.(CD3+.CD19-) panel1 CBCS"
## [1] "IgD-.memory.Bcells.(CD27+) panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD-.memory.Bcells.(CD27+) panel1 FREQ"
##
## 0 1
## 856 19
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD-.memory.Bcells.(CD27+) panel1 CBCS"
## [1] "IgD+.memory.Bcells.(CD27+) panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD+.memory.Bcells.(CD27+) panel1 FREQ"
##
## 0 1
## 856 19
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD+.memory.Bcells.(CD27+) panel1 CBCS"
## [1] "Helper.Tcells-CD4+ panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Helper.Tcells-CD4+ panel1 FREQ"
##
## 0 1
## 927 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Helper.Tcells-CD4+ panel1 CBCS"
## [1] "B.cells.(CD3-.CD19+) panel1 COUNTS"
##
## 0 1
## 848 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "B.cells.(CD3-.CD19+) panel1 FREQ"
##
## 0 1
## 927 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "B.cells.(CD3-.CD19+) panel1 CBCS"
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 CBCS"
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 FREQ"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 CBCS"
## [1] "DC.NK.(CD20-.CD14-) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "DC.NK.(CD20-.CD14-) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "DC.NK.(CD20-.CD14-) panel2 CBCS"
## [1] "MONOCYTES.(CD14+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "MONOCYTES.(CD14+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "MONOCYTES.(CD14+) panel2 CBCS"
## [1] "NK.(CD16+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "NK.(CD16+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "NK.(CD16+) panel2 CBCS"
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 CBCS"
## [1] "NK.CD56HI panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "NK.CD56HI panel2 FREQ"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "NK.CD56HI panel2 CBCS"
## [1] "NK.CD56LO panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "NK.CD56LO panel2 FREQ"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "NK.CD56LO panel2 CBCS"
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 CBCS"
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 CBCS"
## [1] "DC.(HLA-DR+) panel2 COUNTS"
##
## 0 1
## 710 153
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "DC.(HLA-DR+) panel2 FREQ"
##
## 0 1
## 710 153
## [1] "DC.(HLA-DR+) panel2 CBCS"
# results=results[-order(results$METRIC),]
results$COMP_LOOK =gsub(".", " ",results$COMP_LOOK,fixed = TRUE)
write.table(
results,
sep = "\t",
quote = FALSE,
file = paste0(dir,"testResults.txt"),
row.names = FALSE
)